SaaS · Case study

Puppet CloudOps

A multi-cloud FinOps platform: ingest cloud billing across five hyperscalers, surface sub-second spend analytics, and auto-generate Terraform pull requests so customers apply savings through GitOps.

End-to-end owner · LLD author 2024 → 2026

GoClickHouseKafkaKEDAGraphQL FederationTypeScriptReactTerraformKubernetes

The problem

Cloud spend is scattered: every hyperscaler bills in its own format, at its own cadence, in volumes measured in terabytes a day. A FinOps platform has to ingest all of it without losing a row, normalise it into one comparable shape, answer analytical questions over billions of rows fast enough to feel interactive, and then close the loop: turn a recommendation into a change a customer can actually apply. And it has to do all of that multi-tenant and SOC 2-ready from day one.

What I did

I owned Puppet CloudOps end-to-end and authored its low-level design. It shipped through Puppet’s Early Access programme.

SourcesAWS · Azure · GCP · OCI · Kubernetes, FOCUS-normalised

IngestScheduled + SQS event triggers, Kafka, KEDA parser fleet 0→N, DLQ & retry

StoreClickHouse db-per-tenant + materialised views · PostgreSQL schema-per-tenant · Redis

APIGraphQL Apollo Federation supergraph over ~7 Go subgraphs

ActReact + TanStack UI · auto-generated Terraform PRs → GitOps

Five billing formats in, an applyable Terraform pull request out.

Multi-tenant by design. Database-per-tenant in ClickHouse, schema-per-tenant in PostgreSQL, async Kafka messaging, token-auth REST for service-to-service. Tenant isolation was baked in for SOC 2 from the first schema.
Ingest at scale. Terabytes a day, dual-trigger (scheduled + SQS event-driven), with KEDA scaling the parser fleet 0→N on queue backlog under backpressure, plus dead-letter queues and retry. Zero production data-loss.
Sub-second analytics. ClickHouse materialised views, pre-aggregation, Redis caching and query rewriting took p95 from ~20s to sub-second over billions of rows.
GraphQL platform. An Apollo Federation supergraph over ~7 Go (gqlgen) subgraphs, codegen typings into a React + TanStack UI, with reactive state over Redis pub/sub and WebSockets.
Closing the loop. Optimisation recommendations become auto-generated Terraform pull requests, so a customer applies savings through their normal GitOps review, the same way they ship everything else to their IaC.

Impact

p95 analytics latency from ~20 seconds to sub-second over billions of rows.
Zero production data-loss across terabyte-a-day ingest, with elastic 0→N scaling absorbing spend spikes.
Savings delivered as reviewable Terraform PRs, keeping customers’ infra in GitOps where the rest of their changes already live.
A multi-tenant, SOC 2-ready platform spanning five hyperscalers from one normalised FOCUS model.

Where it went

CloudOps shipped through Puppet’s Early Access programme. In 2026 Perforce folded its capabilities, including cloud cost and financial compliance, into Perforce Unified Compliance for Puppet Enterprise Advanced customers.